Fetch time entries from Toggl into searchable documents

Toggl reader is a LlamaIndex integration that fetches time entries from Toggl Track workspaces and projects, converting them into Document objects. It enables developers to pull time-tracking data programmatically using a Toggl API token, with support for filtering by workspace, project, and date range, and formatting output as Markdown.

Use Toggl reader when you need to load time-tracking data into LlamaIndex as Document objects for further processing. It's ideal for scenarios where you want to programmatically retrieve time entries from specific workspaces and projects within a date range.

Do not use this tool if you only need basic Toggl reporting features available in the native interface, or if you're working with time-tracking platforms other than Toggl Track.

You provide a Toggl API token (obtained from your Toggl profile settings), workspace ID, project ID, and a start date for filtering entries. Optionally, you can specify the output format.

You receive an array of Document objects containing time entry data, formatted according to your specified output format (such as Markdown), ready for use within LlamaIndex.

Install the package:

pip install llama-index-readers-toggl

Load time entries from the past week:

from llama_index.readers.toggl import TogglReader
from llama_index.readers.toggl.dto import TogglOutFormat
import datetime

reader = TogglReader(api_token="{{YOUR_API_TOKEN}}")

docs = reader.load_data(
    workspace_id="{{WORKSPACE_ID}}",
    project_id="{{PROJECT_ID}}",
    start_date=datetime.datetime.now() - datetime.timedelta(days=7),
    out_format=TogglOutFormat.markdown,
)

To get your API token: log in to Toggl, open your profile at track.toggl.com/profile, scroll down and click "-- Click to reveal --" for the API token.

This reader integrates with LlamaIndex and works with Toggl Track's API to retrieve time entry data.

Toggl reader is built for developers who need to load time-tracking data from Toggl into LlamaIndex Document format. It's designed for anyone working within the LlamaIndex ecosystem who wants to retrieve time entries programmatically.